Standardized framework for assessing soil quality at antimony smelting site by considering microbial-induced resilience and heavy metal contamination.

Antimony smelting activities damage the soil and vegetation surroundings while generating economic value. However, no standardized methods are available to diagnose the extent of soil degradation at antimony smelting sites. This study developed a standardized framework for assessing soil quality by considering microbial-induced resilience and heavy metal contamination at Xikuangshan antimony smelting site. The soil resilience index (SRI) and soil contamination index (SCI) were calculated by Minimum Data Set and geo-accumulation model, respectively. After standardized by a multi-criteria quantitative procedure of modified Nemerow's pollution index (NPI), the integrated assessment of soil quality index (SQI), which is the minimum of SRINPI and SCINPI, was achieved. The results showed that Sb and As were the prominent metal(loid) pollutants, and significant correlations between SQI and SRI indicated that the poor soil quality was mainly caused by the low level of soil resilience. The primary limiting factors of SRI were Fungi in high and middle contaminated areas, and Skermanella in low contaminated area, suggesting that the weak soil resilience was caused by low specific microbial abundances. Microbial regulation and phytoremediation are greatly required to improve the soil quality at antimony smelting sites from the perspectives of pollution control and resilience improvement. This study improves our understanding of ecological effects of antimony smelting sites and provides a theoretical basis for ecological restoration and sustainable development of mining areas.

Carbon emissions in China's steel industry from a life cycle perspective: Carbon footprint insights.

China is the most important steel producer in the world, and its steel industry is one of the most carbon-intensive industries in China. Consequently, research on carbon emissions from the steel industry is crucial for China to achieve carbon neutrality and meet its sustainable global development goals. We constructed a carbon dioxide (CO2) emission model for China's iron and steel industry from a life cycle perspective, conducted an empirical analysis based on data from 2019, and calculated the CO2 emissions of the industry throughout its life cycle. Key emission reduction factors were identified using sensitivity analysis. The results demonstrated that the CO2 emission intensity of the steel industry was 2.33 ton CO2/ton, and the production and manufacturing stages were the main sources of CO2 emissions, accounting for 89.84% of the total steel life-cycle emissions. Notably, fossil fuel combustion had the highest sensitivity to steel CO2 emissions, with a sensitivity coefficient of 0.68, reducing the amount of fossil fuel combustion by 20% and carbon emissions by 13.60%. The sensitivities of power structure optimization and scrap consumption were similar, while that of the transportation structure adjustment was the lowest, with a sensitivity coefficient of less than 0.1. Given the current strategic goals of peak carbon and carbon neutrality, it is in the best interest of the Chinese government to actively promote energy-saving and low-carbon technologies, increase the ratio of scrap steel to steelmaking, and build a new power system.

Assessment of internal exposure risk from metals pollution of occupational and non-occupational populations around a non-ferrous metal smelting plant.

Non-ferrous metal smelting poses significant risks to public health. Specifically, the copper smelting process releases arsenic, a semi-volatile metalloid, which poses an emerging exposure risk to both workers and nearby residents. To comprehensively understand the internal exposure risks of metal(loid)s from copper smelting, we explored eighteen metal(loid)s and arsenic metabolites in the urine of both occupational and non-occupational populations using inductively coupled plasma mass spectrometry with high-performance liquid chromatography and compared their health risks. Results showed that zinc and copper (485.38 and 14.00 µg/L), and arsenic, lead, cadmium, vanadium, tin and antimony (46.80, 6.82, 2.17, 0.40, 0.44 and 0.23 µg/L, respectively) in workers (n=179) were significantly higher compared to controls (n=168), while Zinc, tin and antimony (412.10, 0.51 and 0.15 µg/L, respectively) of residents were significantly higher than controls. Additionally, workers had a higher monomethyl arsenic percentage (MMA%), showing lower arsenic methylation capacity. Source appointment analysis identified arsenic, lead, cadmium, antimony, tin and thallium as co-exposure metal(loid)s from copper smelting, positively relating to the age of workers. The hazard index (HI) of workers exceeded 1.0, while residents and control were approximately at 1.0. Besides, all three populations had accumulated cancer risks exceeding 1.0 × 10-4, and arsenite (AsIII) was the main contributor to the variation of workers and residents. Furthermore, residents living closer to the smelting plant had higher health risks. This study reveals arsenic exposure metabolites and multiple metals as emerging contaminants for copper smelting exposure populations, providing valuable insights for pollution control in non-ferrous metal smelting.

Metal concentrations in fish, crabs, and bivalve molluscs from marine waters adjacent to a multi-metals smelter and refinery.

Metal concentrations were determined in tissues of finfish, crabs, and bivalve molluscs collected from marine waters near Port Pirie, South Australia, the site of a long-standing multi-metals smelter and refinery. A general trend of tissue metal concentrations in order of highest to lowest was observed in bivalves > crabs > finfish. A lead concentration of 158 ± 6.6 mg/kg (wet wt.) was observed in blue mussels (Mytilus galloprovincialis) sampled close to the smelter. Lead concentrations correlated positively with proximity to the smelter in all biota analysed. Similar relationships were observed for cadmium, copper, zinc and selenium in all biota except razorfish (Pinna bicolor; Bivalvia: Pinnidae), which showed no correlation with proximity to the smelter for these metals. Inorganic arsenic concentrations were below the limit of reporting in the majority of the analysed samples, however inorganic arsenic concentrations in blue swimmer crabs (Portunus armatus) and blue mussels correlated with proximity to the smelter. Mercury concentrations in the biota analysed were generally low and showed variable relationships with proximity to the smelter, with no significant correlation observed in finfish and razorfish, a significant positive correlation in blue mussels, and a significant negative correlation in blue swimmer crabs. This is the first major study of metal concentrations in recreationally-targeted marine species near Port Pirie species for more than two decades. Comparison with data from previous studies conducted shows little change in tissue metal concentrations in marine biota near Port Pirie over the past 40 years.

Chemodiversity of dissolved organic matter and its association with the bacterial community at a zinc smelting slag site after 10 years of direct revegetation.

Dissolved organic matter (DOM) plays a critical role in driving the development of biogeochemical functions in revegetated metal smelting slag sites, laying a fundamental basis for their sustainable rehabilitation. However, the DOM composition at the molecular level and its interaction with the microbial community in such sites undergoing long-term direct revegetation remain poorly understood. This study investigated the chemodiversity of DOM and its association with the bacterial community in the rhizosphere and non-rhizosphere slags of four plant species (Arundo donax, Broussonetia papyrifera, Cryptomeria fortunei, and Robinia pseudoacacia) planted at a zinc smelting slag site for 10 years. The results indicated that the relative abundance of lipids decreased from 18 % to 5 %, while the relative abundance of tannins and lignins/CRAM-like substances increased from 4 % to 10 % and from 44 % to 64 % in the revegetated slags, respectively. The chemical stability of the organic matter in the rhizosphere slag increased due to the retention of recalcitrant DOM components, such as lignins, aromatics, and tannins. As the diversity and relative abundance of the bacterial community increased, particularly within the Proteobacteria, there was better utilization of recalcitrant components (e.g., lignins/CRAM-like compounds), but this utilization was not invariable. In addition, potential preference associations between specific bacterial OTUs and DOM molecules were observed, possibly stimulated by heavy metal bioavailability. Network analysis revealed complex connectivity and strong interactions between the bacterial community and DOM molecules. These specific interactions between DOM molecules and the bacterial community enable adaptation to the harsh conditions of the slag environment. Overall, these findings provide novel insights into the transformation of DOM chemodiversity at the molecular level at a zinc smelting slag sites undergoing long-term revegetation. This knowledge could serve as a crucial foundation for developing direct revegetation strategies for the sustainable rehabilitation of metal smelting slag sites.

Machine vision-based detection of forbidden elements in the high-speed automatic scrap sorting line.

Highly efficient industrial sorting lines require fast and reliable classification methods. Various types of sensors are used to measure the features of an object to determine which output class it belongs to. One technique involves the use of an RGB camera and a machine learning classifier. The paper is focused on protecting the sorting process against prohibited and dangerous items potentially present in the sorted material that pose a threat to the sorting process or the subsequent metallurgical process. To achieve this, a convolutional neural network classifier was applied under real-life conditions to detect forbidden elements in copper-based metal scrap. A laboratory stand simulating the working conditions in a high-speed scrap sorting line was prepared. Using this custom stand, training and test sets for machine learning were gathered and labeled. An image preprocessing algorithm was designed to increase the robustness of the resulting forbidden element detector system. The performance of multiple neural network architectures and data set augmentations was analyzed. The highest accuracy of 98.03% and F1-score of 97.16% were achieved with a DenseNet-based classifier. The results of this paper show the feasibility of using the presented solution on a high-speed industrial line.

Contribution assessment and accumulation prediction of heavy metals in wheat grain in a smelting-affected area using machine learning methods.

Due to the diverse controlling factors and their uneven spatial distribution, especially atmospheric deposition from smelters, assessing and predicting the accumulation of heavy metals (HM) in crops across smelting-affected areas becomes challenging. In this study, integrating HM influx from atmospheric deposition, a boosted regression tree model with an average R2 > 0.8 was obtained to predict accumulation of Pb, As, and Cd in wheat grain across a smelting region. The atmospheric deposition serves as the dominant factor influencing the accumulation of Pb (28.2 %) and As (31.2 %) in wheat grain, but shows a weak influence on Cd accumulation (12.1 %). The contents of available HM in soil affect HM accumulation in wheat grain more significantly than their total contents in soil with relative importance rates of Pb (14.4 % > 8.2 %), As (30.9 % > 4.0 %), and Cd (55.0 % > 16.9 %), respectively. Marginal effect analysis illustrates that HM accumulation in wheat grain begins to intensify when Pb content in atmospheric dust reaches 5140 mg/kg and available Cd content in soil exceeds 1.15 mg/kg. The path analysis rationalizes the cascading effects of distances from study sites to smelting factories on HM accumulation in wheat grain via negatively influencing atmospheric HM deposition. The study provides data support and a theoretical basis for the sustainable development of non-ferrous metal smelting industry, as well as for the restoration and risk management of HM-contaminated soils.

[On the June 25, 2024 Judgment of the Court of Justice of the European Union regarding Ilva Taranto (Southern Italy)]. / Sulla sentenza della Corte di Giustizia dell'Unione europea del 25 giugno 2024 in merito all'Ilva di Taranto.

The June 25, 2024 Judgment of the Court of Justice of the European Union is based on the Industrial Emissions (Integrated Pollution Prevention and Control) Directive 2010/75/EU and confirms its applicability to the Taranto steel plant, reiterating that the concept of pollution includes damage to the environment and human health; the health impact assessment of polluting industrial activities, such as the Ilva steelworks in Southern Italy, must constitute an internal act in the procedures for granting and reviewing the operating permission; all pollutants attributable to the plant that are scientifically recognized as harmful to health must be considered in the assessment procedures. In the case of serious and significant danger to the integrity of the environment and human health, the operation of the installation must be suspended. The Judgment highlights important elements on the level of principle and application, which are extraordinarily useful for environment and health personnel, for open-minded and aware local, regional, and national administrators, and above all for the citizens and communities most exposed to pollutants recognized as harmful to health. Preventive environmental health impact assessments gain renewed strength as tools for evaluative and authorized decision-making on production activities, in a sense of full integration between environment and health. The right to environmental and health protection and prevention is an integral part of the defence of human rights, especially in sacrifice zones such as Taranto and many other sites to be reclaimed, considered by the UN as "places where residents suffer devastating physical and mental health consequences and human rights violations".

Characterization of occupational inhalation exposures to particulate and gaseous straight and water-based metalworking fluids.

Exposure assessments to metalworking fluids (MWF) is difficult considering the complex nature of MWF. This study describes a comprehensive exposure assessment to straight and water-based MWFs among workers from 20 workshops. Metal and organic carbon (OC) content in new and used MWF were determined. Full-shift air samples of inhalable particulate and gaseous fraction were collected and analysed gravimetrically and for metals, OC, and aldehydes. Exposure determinants were ascertained through observations and interviews with workers. Determinants associated with personal inhalable particulate and gaseous fractions were systematically identified using mixed models. Similar inhalable particle exposure was observed for straight and water-based MWFs (64-386 µg/m3). The gaseous fraction was the most important contributor to the total mass fraction for both straight (322-2362 µg/m3) and water-based MWFs (101-699 µg/m3). The aerosolized particles exhibited low metal content irrespective of the MWF type; however, notable concentrations were observed in the sumps potentially reaching hazardous concentrations. Job activity clusters were important determinants for both exposure to particulate and gaseous fractions from straight MWF. Current machine enclosures remain an efficient determinant to reduce particulate MWF but were inefficient for the gaseous fraction. Properly managed water-based MWF meaning no recycling and no contamination from hydraulic fluids minimizes gaseous exposure. Workshop temperature also influenced the mass fractions. These findings suggest that exposures may be improved with control measures that reduce the gaseous fraction and proper management of MWF.

Removal of the heavy metals from copper slag by using carbonless additives.

The smelting processes account for over 80 % of global copper production, generating various slags in large quantities. Most of these slags do not contain the required amounts of valuable metals to justify economic revalorization, yet the concentrations present may negatively affect the environment. In this study, heavy and potentially toxic metals were removed by keeping the liquefied slag at 1300 °C for four hours, while the metals gathering was enhanced by adding silicon-copper compounds. Crystallography, metallography, gravimetric, thermogravimetric, and differential thermal analysis were employed to characterize the slag. Electron probe microanalysis was utilized to examine the distribution of heavy and potentially toxic metals from the original copper slag to the remaining slag and mattes formed in the lower portion of the containing vessel. In all instances, concentrations of the arsenic and zinc were reduced below the detection limit. Moreover, the cumulative concentrations of six heavy metals were reduced from 2400 ppm in the initial slag to 41.7 ppm in the remaining slag when using 30 wt%Si70wt%Cu additive. All potentially valuable or toxic metals gathered in the mattes that had oxygen concentrations about 50 times lower than in the initial slag, at 0.82, 0.56, and 0.68 wt% after the mixing slag with 10 wt%Si90%Cu, 30 wt%Si70wt%Cu, and 50 wt%Si50wt%Cu additives, respectively. Investigated practices can mitigate the threat of heavy and potentially toxic metals associated with the disposal of copper slags while also enabling the recovery of valuable metals and rendering the remaining slag suitable for construction or mine backfill purposes.

Metal distribution in three organs and edibility assessment on Coptodon rendalli from the Umgeni River impacted by metallurgic industrial activities.

Fish is among the most affordable and readily available protein sources for communities residing near water bodies. However, the recent pollution status of aquatic ecosystems has rendered fish consumption risky for human health. The study evaluated metal levels in the liver, gill, and muscle tissues of Redbreast tilapia (Coptodon rendalli) from Inanda and Nagle dams in the uMgeni River system. Metals, Al, Sb, Cd, Cr, Fe, Mn, Mo, Pb, and Zn were analysed using ICP-OES. Fish size showed no significant difference between the two dams (p > 0.05) whereas a descending trend liver > gill > muscle was observed for most metal levels at both dams. Moreover, there was a clear separation for metal levels in the liver, gill, and muscle between the two dams (p < 0.001) and a similar trend was observed for organs in each dam (p < 0.001). No relationship was observed between fish length and metal levels and no definite trend was observed for inter-metal relationships. Antimony, Cr, and Pb showed THQs greater than 1 at both dams which suggests health risks for consumers. Molybdenum has also shown a concerning THQs with some individuals exhibiting values ranging from 0.5 - 0.9. These findings suggest that consuming C. rendalli from the Inanda and Nagle dams could result in adverse health effects from Sb, Cr and Pb.

Deep-sea microorganisms-driven V5+ and Cd2+ removal from vanadium smelting wastewater: Bacterial screening, performance and mechanism.

The disorderly discharge of industrial wastewater containing heavy metals has caused serious water pollution and ecological environmental risks, ultimately threatening human life and health. Biological treatment methods have obvious advantages, but the existing microorganisms exhibit issues such as poor resistance, adaptability, colonization ability, and low activity. However, a wide variety of microorganisms in deep-sea hydrothermal vent areas are tolerant to heavy metals, possessing the potential for efficient treatment of heavy metal wastewater. Based on this, the study obtained a group of deep-sea microbial communities dominated by Burkholderia-Caballeronia-Paraburkholderia through shake flask experiments from the sediments of deep-sea hydrothermal vents, which can simultaneously achieve the synchronous removal of vanadium and cadmium heavy metals through bioreduction, biosorption, and biomineralization. Through SEM-EDS, XRD, XPS, and FT-IR analyses, it was found that V(V) was reduced to V(IV) through a reduction process and subsequently precipitated. Glucose oxidation accelerated this process. Cd(II) underwent biomineralization to form precipitates such as cadmium hydroxide and cadmium carbonate. Functional groups on the microbial cell surface, such as -CH2, C=O, N-H, -COOH, phosphate groups, amino groups, and M-O moieties, participated in the bioadsorption processes of V(V) and Cd(II) heavy metals. Under optimal conditions, namely a temperature of 40 °C, pH value of 7.5, inoculation amount of 10%, salinity of 4%, COD concentration of 600 mg/L, V5+ concentration of 300 mg/L, and Cd2+ concentration of 40 mg/L, the OD600 can reach its highest at 72 h, with the removal efficiency of V5+, Cd2+, and COD in simulated vanadium smelting wastewater reaching 86.32%, 59.13%, and 61.63%, respectively. This study provides theoretical insights and practical evidence for understanding the dynamic changes in microbial community structure under heavy metal stress, as well as the resistance mechanisms of microbial treatment of industrial heavy metal wastewater.

The influence of chlorination additives on metal separation during the pyrometallurgical recovery of spent lithium-ion batteries.

The difficulty of separating Li during pyrometallurgical smelting of spent lithium-ion batteries (LIBs) has limited the development of pyrometallurgical processes. Chlorination enables the conversion of Li from spent LIBs to the gas phase during the smelting process. In this paper, the effects of four solid chlorinating agents (KCl, NaCl, CaCl2 and MgCl2) on Li volatilization and metal (Co, Cu, Ni and Fe) recovery were investigated. The four solid chlorinating agents were systematically compared in terms of the direct chlorination capacities, indirect chlorination capacities, alloy physical losses and chemical losses in the slag. CaCl2 was better suited for use as a solid chlorinating agent to promote Li volatilization due to its excellent results in these indexes. The temperature required for the release of HCl from MgCl2, facilitated by CO2 and SiO2, was lower than 500 °C. The prematurely released HCl failed to participate in the chlorination reaction. This resulted in approximately 12 % less Li volatilization when MgCl2 was used as a chlorinating agent compared to when CaCl2 was used. In addition, the use of KCl as a chlorinating agent decreased the chemical dissolution loss of alloys in the slag. The performance of NaCl was mediocre. Finally, based on evaluations of the four indexes, recommendations for the selection and optimization of solid chlorinating agents were provided.

Experimental and DFT calculation study on the efficient removal of high fluoride wastewater from metallurgical wastewater by kaolinite.

Fluoride pollution and water scarcity are urgent issues. Reducing fluoride concentration in water is crucial. Kaolinite has been used to study adsorption and fluoride removal in water and to characterize material properties. The experimental results showed that the adsorption capacity of kaolinite decreased with increasing pH. The highest adsorption of fluoride occurred at pH 2, with a capacity of 11.1 mg/g. The fluoride removal efficiency remained high after four regeneration cycles. The fitting results with the Freundlich isotherm model and the external diffusion model showed that the non-homogeneous adsorption of kaolinite fit the adsorption behavior better. Finally, the adsorption mechanism was analyzed by FT-IR and XPS. The binding energies of various adsorption sites and the chemical adsorption properties of atomic states were discussed in relation to DFT calculations. The results showed that Al and H sites were the main binding sites, and the bonding stability for different forms of fluoride varies, with the size of Al-F (-7.498 eV) > H-F (-6.04 eV) > H-HF (-3.439 eV) > Al-HF (-3.283 eV). Furthermore, the density of states and Mulliken charge distribution revealed that the 2p orbital of F was found to be active in the adsorption process and was the main orbital for charge transfer.

Polymetallic contamination drives indigenous microbial community assembly dominated by stochastic processes at Pb-Zn smelting sites.

Indigenous microbial communities in smelting areas are crucial for maintaining fragile ecosystem functions. However, the community assembly process and their responses to polymetallic pollution are poorly understood, especially the taxa in each bin from the amplicons that contributed to the assembly process. Herein, microbial diversity, co-occurrence patterns, assembly process and the intrinsic mechanisms across contamination gradients at a typical PbZn smelting site were systematically unravelled by high-throughput sequencing. The results showed a consistent compositional profile among the indigenous communities across sampling sites, wherein genera KD4-96 from Chloroflexi and Sphingomonas from Proteobacteria emerged as the most abundant taxa. Network modularity of the high- and middle-contaminated communities at Pb and Zn smelting sites was >0.44, indicating that community populations were clustered into modules to resist high heavy metal stress. Stochastic processes dominated the community assembly, with the greatest contribution from drift (DR), which was significantly correlated with Pb, Zn, Cr and Cu contents. What's particular was that the DR-controlled bins were dominated by Proteobacteria (typical r-strategists), while the HoS-controlled bins were by Chloroflexi (typical K-strategists). Furthermore, the proportion of DR in the bins dominated by Sphingomonadaceae (phylum Proteobacteria) increased gradually with the increase of heavy metal contents. These discoveries provide essential insights for community control in restoring and mitigating soil degradation at PbZn smelting sites.

Characteristics and risk assessment of heavy metals in groundwater at a typical smelter-contaminated site in Southwest China.

To explore the characteristics and evaluate the risk of heavy metals in groundwater at a typical smelter-contaminated site, this study focuses on a representative a historical arsenic smelting plant in Southwest China, where the primary historical products were metallic arsenic (∼1000 tons/year) and arsenic trioxide (∼2000 ton/year). The results demonstrated As and Pb as the main pollutants in soil, and As and Cd as main pollutants in groundwater through soil profiling and quarterly groundwater analysis. The maximum As and Pb in the surface soil were 76800 and 2290 mg/kg, respectively, with As vertically infiltrating the deep gravel-sand layer (18-20 m). The groundwater pollution distribution progressively increased along flow direction, influenced by seasonal surface runoff and infiltration fluctuations. The groundwater pollutant concentrations during the dry season notably surpassed those during the wet season, with maximum As and Cd concentrations of 111.64 mg/L and 19.85 µg/L during the dry season, respectively. Furthermore, the analytic hierarchy process (AHP) was applied to evaluate the comprehensive risk of contaminated-site across pollution source load, regional groundwater intrinsic vulnerability, and evaluation of nearby sensitive receptors. The results revealed that the carcinogenic risk of lead in surface soil was moderate to high, while arsenic posed a high carcinogenic risk, contributing to an overall carcinogenic risk proportion of 89.6% in surface soil. Exposure through groundwater intake was identified as the primary pathway, with carcinogenic and noncarcinogenic risks exceeding those through skin contact. The final weights result demonstrated that the principal risk factors are the intrinsic arsenic load and protective target characteristics of regional groundwater at this site. This study provides a reference for comprehensive assessments of similarly contaminated industrial and smelting sites.

Pollution-related changes in nest microbiota: Implications for growth and fledging in three passerine birds.

Non-ferrous smelters emit toxic metals into the environment, posing a threat to wildlife health. Despite the acknowledged role of microbes in host health, the impact of such emissions on host-associated microbiota, especially in wild birds, remains largely unexplored. This study investigates the associations of metal pollution, fitness, and nest microbiota (serving as a proxy for early-life microbial environment) which may influence the nestling health and development. Our study focuses on three passerine birds, the great tit (Parus major), blue tit (Cyanistes caeruleus), and pied flycatcher (Ficedula hypoleuca), within control and metal-polluted sites around a Finnish copper-nickel smelter. The polluted sites had been contaminated with arsenic (As), cadmium (Cd), copper (Cu), nickel (Ni), and zinc (Zn). We performed bacterial 16S rRNA sequencing and metal analyses on 90 nests and monitored nestling body mass, fledging success, and various biotic and abiotic factors. Our findings revealed species-specific responses to metal exposure in terms of both fitness and nest microbiota. P. major and C. caeruleus showed sensitivity to pollution, with decreased nestling growth and fledging in the polluted zone. This was accompanied by a shift in the bacterial community composition, which was characterized by an increase in some pathogenic bacteria (in P. major and C. caeruleus nests) and by a decrease in plant-associated bacteria (within C. caeruleus nests). Conversely, F. hypoleuca and their nest microbiota showed limited responses to pollution, indicating greater tolerance to pollution-induced environmental changes. Although pollution did not correlate with nest alpha diversity or the most abundant bacterial taxa across all species, certain potential pathogens within the nests were enriched in polluted environments and negatively correlated with nestling fitness parameters. Our results suggest that metal pollution may alter the nest bacterial composition in some bird species, either directly or indirectly through environmental changes, promoting pathogenic bacteria and potentially impacting bird survival.

Vertical transport velocity of fine particles of aluminum smelter emissions.

In this study, the average values of vertical velocity of particles emitted from an aluminum smelter in the surface layer of the atmosphere were estimated using a semi-empirical method. The method is based on regression analysis of the horizontal profile of pollutants measured along the selected direction using moss bioindicators. The selection of epiphytic mosses Sanionia uncinata was carried out in 2013 in the zone of influence of a metallurgical industry enterprise in the city of Kandalaksha, Murmansk region. The concentrations of As, Si, Ni, Zn, Ti, Cd, Na, Pb, Co, K, Ba, Ca, Mg, Mn, Sr, Fe, Al, V, Cr, Cu were determined using atomic emission spectrometry. The conducted assessments showed that the average particle velocity toward the Earth's surface, when considering large spatial and temporal scales, is tens of times higher than gravitational settling velocities.

Source Apportionment of Particulate Matter in a Metal Workshop.

Metal workshops are workplaces with the substantial production of particulate matter (PM) with high metal content, which poses a significant health risk to workers. The PM produced by different metal processing techniques differs considerably in its elemental composition and size distribution and therefore poses different health risks. In some previous studies, the pollution sources were isolated under controlled conditions, while, in this study, we present a valuable alternative to characterize the pollution sources that can be applied to real working environments. Fine PM was sampled in five units (partially specializing in different techniques) of the same workshop. A total of 53 samples were collected with a temporal resolution of 30 min and 1 h. The mass concentrations were determined gravimetrically, and the elemental analysis, in which the concentrations of 14 elements were determined, was carried out using the X-ray fluorescence technique. Five sources of pollution were identified: background, steel grinding, metal active gas welding, tungsten inert gas welding, and machining. The sources were identified by positive matrix factorization, a statistical method for source apportionment. The identified sources corresponded well with the work activities in the workshop and with the actual sources described in previous studies. It is shown that positive matrix factorization can be a valuable tool for the identification and characterization of indoor sources.

Bronze age Northern Eurasian genetics in the context of development of metallurgy and Siberian ancestry.

The Eurasian Bronze Age (BA) has been described as a period of substantial human migrations, the emergence of pastoralism, horse domestication, and development of metallurgy. This study focuses on two north Eurasian sites sharing Siberian genetic ancestry. One of the sites, Rostovka, is associated with the Seima-Turbino (ST) phenomenon (~2200-1900 BCE) that is characterized by elaborate metallurgical objects found throughout Northern Eurasia. The genetic profiles of Rostovka individuals vary widely along the forest-tundra Siberian genetic cline represented by many modern Uralic-speaking populations, and the genetic heterogeneity observed is consistent with the current understanding of the ST being a transcultural phenomenon. Individuals from the second site, Bolshoy Oleni Ostrov in Kola, in comparison form a tighter cluster on the Siberian ancestry cline. We further explore this Siberian ancestry profile and assess the role of the ST phenomenon and other contemporaneous BA cultures in the spread of Uralic languages and Siberian ancestry.